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Abstract Echinococcus multilocularisis a zoonotic cestode that uses canids as definitive hosts and rodents as intermediate hosts. In humans, this parasite is the causative agent of alveolar echinococcosis. Recently, its range has been expanding across the Northern Hemisphere, and it is increasingly detected in wild canids, domestic dogs, and humans across Canada and the United States. While this expansion has been documented in isolated studies across the continent, a lack of routine sampling in wildlife hinders our ability to anticipate and mitigate further spread ofE. multilocularis. We confirmed the presence ofE. multilocularisin Washington State, USA, using a combination of morphological and molecular techniques across carcasses and field-collected scats of coyotes (Canis latrans), this region’s most common wild canid. Morphological identification of adult worms was confirmed by next-generation sequencing. Over a third of all samples tested positive forE. multiloculariswhen all methodologies were combined. Sequencing revealed a haplotype ofE. multilocularismatching a documented haplotype originally of European origin in British Columbia, Canada. Our study provides the first confirmation ofE. multilocularisin a wild host on the west coast of the U.S and provides additional haplotype information crucial to tracking the geographical expansion of the parasite. We also provide a new next-generation sequencing primer targeting cestodes of canids. The difference in amplification between intestinal and fecal samples suggests that non-invasive fecal sampling using DNA metabarcoding—a popular method of helminth surveillance —may lead to underestimation of prevalence, hindering control measures. The global significance of these findings extends beyond North America;E. multilocularisis a major public health concern in Europe and Asia, where alveolar echinococcosis is increasingly diagnosed in humans. Our study highlights the urgent need for increased surveillance and improved diagnostic strategies worldwide, particularly in regions with significant human-wildlife contact. Author summaryParasites that are transmitted between wildlife, domestic animals, and people are an important part of global health. One such parasite isEchinococcus multilocularis, a small tapeworm of canids that can cause a severe, life-threatening disease in humans called alveolar echinococcosis. Many wild canid hosts of the parasite, such as coyotes, overlap significantly with domestic dogs, which facilitates transmission to humans. In Europe, Asia, and Arctic regions of North America,E. multilocularishas long been recognized as a major public health problem. In recent decades its range has expanded across the Northern Hemisphere, raising concern. In this study, we discoveredE. multilocularisin coyotes in a densely populated area of Washington State, USA — the first detection ofE. multilocularisin a wild host in the region. More than one-third of our coyote samples containedE. multilocularis, confirming that it is widespread in the area. Genetic testing showed that the strain we detected matched one previously found in Canada, originally from Europe. Our findings underscore the importance of monitoringE. multilocularisand other parasites in wildlife so that emerging public health threats can be detected early, reducing risk to people and pets. 

Abstract Contributory science—including citizen and community science—allows scientists to leverage participant‐generated data while providing an opportunity for engaging with local community members. Data yielded by participant‐generated biodiversity platforms allow professional scientists to answer ecological and evolutionary questions across both geographic and temporal scales, which is incredibly valuable for conservation efforts.The data reported to contributory biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological variables, leading to biased data. Though empirical work has highlighted the biases in contributory data, little work has articulated how biases arise in contributory data and the societal consequences of these biases.We present a conceptual framework illustrating how social and ecological variables create bias in contributory science data. In this framework, we present four filters—participation,detectability,samplingandpreference—that ultimately shape the type and location of contributory biodiversity data. We leverage this framework to examine data from the largest contributory science platforms—eBird and iNaturalist—in St. Louis, Missouri, the United States, and discuss the potential consequences of biased data.Lastly, we conclude by providing several recommendations for researchers and institutions to move towards a more inclusive field. With these recommendations, we provide opportunities to ameliorate biases in contributory data and an opportunity to practice equitable biodiversity conservation. Read the freePlain Language Summaryfor this article on the Journal blog.